| 正文 | Business decisionmakers are increasingly using predictive social media analytic tools in forecasting exercises but ignoring potential model uncertainty. Using data on the universe of Twittermessages, we calculate the sentiment regarding each film to understand whether these opinions affect box office opening and DVD retail sales. Our results contrasting eleven different econometric strategies including penalization methods indicate that accounting for model uncertainty can lead to large gains in forecast accuracy. While penalization methods do not outperform model averaging on forecast accuracy, evidence indicates they perform equivalently at the variable selection stage. Finally, incorporating social media data greatly improves forecast accuracy. |
